Statistical Smoothing Methods: Some Practical Aspects.

1987 ◽  
Author(s):  
B. W. Silverman ◽  
C. Jennison
Keyword(s):  
Smoothing Methods

Smoothing Facilitates the Detection of Coupled Responses in Psychophysiological Time Series

2000 ◽  
Vol 14 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Joni Kettunen ◽  
Niklas Ravaja ◽  
Liisa Keltikangas-Järvinen
Keyword(s):  
Time Series ◽  
Type I Error ◽  
Electrodermal Activity ◽  
Moving Average ◽  
Type I ◽  
Facial Electromyography ◽  
Response Characteristics ◽  
Smoothing Methods ◽  
Response Systems ◽  
Different Response

Abstract We examined the use of smoothing to enhance the detection of response coupling from the activity of different response systems. Three different types of moving average smoothers were applied to both simulated interbeat interval (IBI) and electrodermal activity (EDA) time series and to empirical IBI, EDA, and facial electromyography time series. The results indicated that progressive smoothing increased the efficiency of the detection of response coupling but did not increase the probability of Type I error. The power of the smoothing methods depended on the response characteristics. The benefits and use of the smoothing methods to extract information from psychophysiological time series are discussed.

scholarly journals Suppression of stochastic pulsation in laser–plasma interaction by smoothing methods

1993 ◽  
Vol 11 (1) ◽  
pp. 177-184 ◽  
Author(s):  
M. Aydin ◽  
H. Hora
Keyword(s):  
Laser Plasma ◽  
Fusion Energy ◽  
Laser Interaction ◽  
Direct Drive ◽  
Question Mark ◽  
Plasma Interaction ◽  
Laser Plasma Interaction ◽  
Smoothing Methods ◽  
Plasma Corona ◽  
Interaction Problem

Smoothing of laser-plasma interaction by ISI, RPP, SSD, etc. was mainly directed to overcome lateral nonuniformity of irradiation. While these problems are in no way less important, we derived numerically the model of the Laue rippling and hydrorelaxation model for explanation of the measured temporal pulsation in the 10- to 40-ps range and how the smoothing schemes suppress these pulsations. The partial standing wave fields of the normally coherent laser-irradiated plasma corona is then suppressed by smoothing and conclusion for tests for this model, e.g., by the “question mark experiment” is given. The result provides a physics solution of the laser interaction problem for direct-drive inertial fusion energy

scholarly journals Penalty and Smoothing Methods for Convex Semi-Infinite Programming

2009 ◽  
Vol 34 (2) ◽  
pp. 303-319 ◽  
Author(s):  
Alfred Auslender ◽  
Miguel A. Goberna ◽  
Marco A. López
Keyword(s):  
Smoothing Methods ◽  
Infinite Programming

scholarly journals CELLULAR NETWORK TRAFFIC PREDICTION USING EXPONENTIAL SMOOTHING METHODS

2018 ◽  
Author(s):  
Quang Thanh Tran ◽  
Li Jun Hao ◽  
Quang Khai Trinh
Keyword(s):  
Network Traffic ◽  
Cellular Network ◽  
Low Cost ◽  
Real Data ◽  
Exponential Smoothing ◽  
High Accuracy ◽  
Training Data ◽  
Traffic Prediction ◽  
Data Traffic ◽  
Smoothing Methods

Wireless traffic prediction plays an important role in network planning and management, especially for real-time decision making and short-term prediction. Systems require high accuracy, low cost, and low computational complexity prediction methods. Although exponential smoothing is an effective method, there is a lack of use with cellular networks and research on data traffic. The accuracy and suitability of this method need to be evaluated using several types of traffic. Thus, this study introduces the application of exponential smoothing as a method of adaptive forecasting of cellular network traffic for cases of voice (in Erlang) and data (in megabytes or gigabytes). Simple and Error, Trend, Seasonal (ETS) methods are used for exponential smoothing. By investigating the effect of their smoothing factors in describing cellular network traffic, the accuracy of forecast using each method is evaluated. This research comprises a comprehensive analysis approach using multiple case study comparisons to determine the best fit model. Different exponential smoothing models are evaluated for various traffic types in different time scales. The experiments are implemented on real data from a commercial cellular network, which is divided into a training data part for modeling and test data part for forecasting comparison. This study found that ETS framework is not suitable for hourly voice traffic, but it provides nearly the same results with Holt–Winter’s multiplicative seasonal (HWMS) in both cases of daily voice and data traffic. HWMS is presumably encompassed by ETC framework and shows good results in all cases of traffic. Therefore, HWMS is recommended for cellular network traffic prediction due to its simplicity and high accuracy.  

scholarly journals Yield Curve Estimation by Kernel Smoothing Methods

2000 ◽  
Author(s):  
Oliver B. Linton ◽  
Enno Mammen ◽  
Jens Perch Nielsen ◽  
Carsten Tanggaard
Keyword(s):  
Kernel Smoothing ◽  
Yield Curve ◽  
Curve Estimation ◽  
Smoothing Methods
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